The role of competing risks in the analysis of time-to-event data is increasingly acknowledged. Software is readily available. However, confusion remains regarding the proper analysis: When and how do I need to take the presence of competing risks into account? Which quantities are relevant for my research question? How can they be estimated and what assumptions do I need to make? The main quantities in a competing risks analysis are the cause-specific cumulative incidence, the cause-specific hazard, and the subdistribution hazard. We describe their nonparametric estimation, give an overview of regression models for each of these quantities, and explain their difference in interpretation. We discuss the proper analysis in relation to the type of study question, and we suggest software in R and Stata. Our focus is on competing risks analysis in medical research, but methods can equally be applied in other fields like social science, engineering, and economics.

中文翻译：

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风险竞争：概念、方法和软件


竞争风险在事件发生时间数据分析中的作用越来越受到认可。软件很容易获得。然而，关于正确的分析仍然存在困惑：我何时以及如何需要考虑竞争风险的存在？哪些数量与我的研究问题相关？如何估计它们，我需要做出哪些假设？竞争风险分析中的主要数量是特定于原因的累积发生率、特定于原因的危害和子分布危害。我们描述了它们的非参数估计，概述了每个量的回归模型，并解释了它们在解释上的差异。我们讨论了与研究问题类型相关的适当分析，并建议使用 R 和 Stata 中的软件。我们的重点是医学研究中的竞争风险分析，但方法同样可以应用于社会科学、工程和经济学等其他领域。